Bagging different instead of similar models for regression and classification problems
by Sotiris B. Kotsiantis, Dimitris N. Kanellopoulos
International Journal of Computer Applications in Technology (IJCAT), Vol. 37, No. 1, 2010

Abstract: Even though many ensemble techniques have been proposed, there is as yet no clear picture of which method is best. In this study, we propose a technique that uses different subsets of the same training dataset with the concurrent usage of a voting (for classification problems) or averaging methodology (for regression problems) for combining different learners instead of similar learners. We performed a comparison of the proposed ensemble with other well known ensembles that use the same base learners and the proposed technique had better accuracy in most cases.

Online publication date: Thu, 17-Dec-2009

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